World's Best Scientists 2026 revealed!
Yves Moreau

Yves Moreau

D-Index & Metrics

Engineering and Technology

D-Index
65
Citations
29435
World Ranking
1483
National Ranking
15

Genetics

D-Index
75
Citations
32739
World Ranking
1869
National Ranking
29

Research.com Recognitions

  • 2018 - Fellow of the International Society for Computational Biology

Overview

Yves Moreau is affiliated with KU Leuven in Belgium and works primarily within the fields of Biochemistry, Genetics and Molecular Biology, Medicine, and Computer Science. Their research spans various interdisciplinary areas, notably Molecular Biology, Artificial Intelligence, Genetics, Computational Theory and Mathematics, and Pathology and Forensic Medicine.

The scientist's work covers key topics including Computational Drug Discovery Methods, Multiple Sclerosis Research Studies, Cancer Genomics and Diagnostics, Bioinformatics and Genomic Networks, Machine Learning in Materials Science, SARS-CoV-2 and COVID-19 Research, and Genomics and Phylogenetic Studies.

Yves Moreau has authored papers published in a range of scientific journals and preprint archives with substantial output in venues such as arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), European Journal of Human Genetics, Bioinformatics, and Scientific Reports.

Frequent co-authors include Daniele Raimondi, Edward De Brouwer, Ádám Arany, Liesbet M. Peeters, and Ashkan Pirmani, indicating collaborative work in related scientific domains.

Recent publications include:

  • Drug repositioning or target repositioning: A structural perspective of drug-target-indication relationship for available repurposed drugs, 2020, Computational and Structural Biotechnology Journal
  • The use of polygenic risk scores in pre-implantation genetic testing: an unproven, unethical practice, 2021, European Journal of Human Genetics
  • MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information, 2023, Journal of Chemical Information and Modeling
  • ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning, 2020, Journal of Chemical Information and Modeling
  • COVID-19 in people with multiple sclerosis: A global data sharing initiative, 2020, Multiple Sclerosis Journal

Yves Moreau was awarded the Fellow of the International Society for Computational Biology in 2018, recognizing contributions to computational biology through this professional distinction.

Best Publications

  • PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences

    Magali Lescot;Patrice Déhais;Gert Thijs;Kathleen Marchal

  • BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis

    Steffen Durinck;Yves Moreau;Arek Kasprzyk;Sean Davis

  • DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources

    Helen V. Firth;Shola M. Richards;A. Paul Bevan;Stephen Clayton

  • Gene prioritization through genomic data fusion.

    Stein Aerts;Diether Lambrechts;Sunit Maity;Peter Van Loo

  • A human phenome-interactome network of protein complexes implicated in genetic disorders

    Kasper Lage;E Olof Karlberg;Zenia M Størling;Páll Í Ólason

  • CHROMOSOME INSTABILITY IS COMMON IN HUMAN CLEAVAGE-STAGE EMBRYOS

    Evelyne Vanneste;Thierry Voet;Cédric Le Caignec;Cédric Le Caignec;Michèle Ampe

  • GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks.

    Thomas Moerman;Thomas Moerman;Sara Aibar Santos;Carmen Bravo González-Blas;Jaak Simm;Jaak Simm

  • A higher-order background model improves the detection of promoter regulatory elements by Gibbs sampling.

    Gert Thijs;Magali Lescot;Kathleen Marchal;Stephane Rombauts

  • A Gibbs sampling method to detect overrepresented motifs in the upstream regions of coexpressed genes.

    Gert Thijs;Kathleen Marchal;Magali Lescot;Stephane Rombauts

  • Computational tools for prioritizing candidate genes: boosting disease gene discovery

    Yves Moreau;Léon-Charles Tranchevent

  • A Gibbs sampling method to detect over-represented motifs in the upstream regions of co-expressed genes

    Gert Thijs;Kathleen Marchal;Magali Lescot;Stephane Rombauts

  • From hype to reality: data science enabling personalized medicine

    Holger Fröhlich;Rudi Balling;Niko Beerenwinkel;Oliver Kohlbacher

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks

    Olivier Gevaert;Frank De Smet;Dirk Timmerman;Yves Moreau

  • ACE-inhibition induces a cardioprotective transcriptional response in the metabolic syndrome heart

    Aziza Yakubova;Lieven Thorrez;Dmitry Svetlichnyy;Liesbeth Zwarts

  • Emerging patterns of cryptic chromosomal imbalance in patients with idiopathic mental retardation and multiple congenital anomalies: a new series of 140 patients and review of published reports

    B. Menten;N. Maas;B. Thienpont;K. Buysse

  • Versatile Gene-Specific Sequence Tags for Arabidopsis Functional Genomics: Transcript Profiling and Reverse Genetics Applications

    Pierre Hilson;Joke Allemeersch;Thomas Altmann;Sébastien Aubourg

  • Biclustering microarray data by Gibbs sampling.

    Qizheng Sheng;Yves Moreau;Bart De Moor

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • Optimized Data Fusion for Kernel k-Means Clustering

    Shi Yu;Leon-Charles Tranchevent;Xinhai Liu;W. Glanzel

  • Chromosome Instability Is Common in Human Cleavage-Stage Embryos

    Evelyne Vanneste;Thierry Voet;Cedric Le Caginec;Michele Ampe

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Bart De Moor
Bart De Moor KU Leuven
Thierry Voet
Thierry Voet KU Leuven
Thomas D'Hooghe
Thomas D'Hooghe Yale University
Stein Aerts
Stein Aerts KU Leuven
Peter Van Loo
Peter Van Loo The Francis Crick Institute
Kathleen Marchal
Kathleen Marchal Ghent University

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